Cross-mode stabilized stochastic shallow water systems using stochastic finite element methods
Cross-mode stabilized stochastic shallow water systems using stochastic finite element methods
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DOI：
10.1016/j.cma.2022.115873
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发表时间：
2023-01-17
影响因子：
7.2
通讯作者：
Valseth, Eirik
中科院分区：
文献类型：
--
作者：
Chen, Chen;Dawson, Clint;Valseth, Eirik
开发替代模型来研究水文系统中的不确定性，需要在开发采样策略和正演模型模拟方面做出重大努力。此外，在预测时间至关重要的应用中，例如飓风风暴潮的预测，可能需要在短时间内预测系统响应和不确定性。在这里，我们开发了一个有效的随机浅水模型来解决这些问题。为了离散物理和概率空间，我们使用随机伽辽金方法和增量压力修正方案来及时推进解决方案。为了克服离散稳定性问题，我们提出了交叉模式稳定方法，它采用现有的稳定方法在概率空间中，通过增加稳定项，以模式耦合的方式，每个随机模式。我们广泛地验证了开发的方法，理想化的浅水测试案例和过去的飓风后报。随后，我们使用开发和验证的方法进行全面的统计分析建立浅水代理模型。最后，我们提出了一个不确定的风阻力系数下的飓风风暴潮预报，并证明了它的有效性飓风艾克和哈维。(c)2023 Elsevier B.V.保留所有权利。
The development of surrogate models to study uncertainties in hydrologic systems requires significant effort in the development of sampling strategies and forward model simulations. Furthermore, in applications where prediction time is critical, such as prediction of hurricane storm surge, the predictions of system response and uncertainties can be required within short time frames. Here, we develop an efficient stochastic shallow water model to address these issues. To discretize the physical and probability spaces we use a Stochastic Galerkin method and an Incremental Pressure Correction Scheme to advance the solution in time. To overcome discrete stability issues, we propose cross-mode stabilization methods which employs existing stabilization methods in the probability space by adding stabilization terms to every stochastic mode in a modes-coupled way. We extensively verify the developed method for both idealized shallow water test cases and hindcasting of past hurricanes. We subsequently use the developed and verified method to perform a comprehensive statistical analysis of the established shallow water surrogate models. Finally, we propose a predictor for hurricane storm surge under uncertain wind drag coefficients and demonstrate its effectivity for Hurricanes Ike and Harvey.(c) 2023 Elsevier B.V. All rights reserved.